To come full circle, we need to reexamine deepDMD and compare it to these models. DeepDMD uses a feedforward neural network to simultaneously parameterize the matrix \(K\)  as well as the dictionary functions \(\psi (y)\) . deepDMD has built accurate predictive models and its dimension (\(N\in \mathbb {Z}^+\) ) scales well with that of the modeled system [1]}. We build a novel comparison of deepDMD and a much lower-parameter model built from the augSILL basis. The lower parameter augSILL model learns as quickly and accurately as the deep-learning-based model.
